Overview

Dataset statistics

Number of variables94
Number of observations242572
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory151.3 MiB
Average record size in memory654.0 B

Variable types

Numeric25
Categorical55
Boolean14

Alerts

destroyedTopBaseTurret has constant value "0"Constant
destroyedMidBaseTurret has constant value "0"Constant
lostTopBaseTurret has constant value "0"Constant
lostMidBaseTurret has constant value "0"Constant
champLevelDiff has 26804 (11.0%) zerosZeros
wardsDestroyed has 5013 (2.1%) zerosZeros
wardsLost has 5548 (2.3%) zerosZeros
destroyedInhibitors has 218455 (90.1%) zerosZeros
lostInhibitors has 219211 (90.4%) zerosZeros
totalKilledObjectives has 51268 (21.1%) zerosZeros
totalLostObjectives has 49181 (20.3%) zerosZeros
totalGameKilledObjectives has 5812 (2.4%) zerosZeros
totalLostTurrets has 95544 (39.4%) zerosZeros
totalDestroyedTurrets has 92814 (38.3%) zerosZeros
totalLostStructures has 95505 (39.4%) zerosZeros
totalDestroyedStructures has 92761 (38.2%) zerosZeros
totalGameDestroyedStructures has 56534 (23.3%) zerosZeros

Reproduction

Analysis started2022-12-14 19:29:35.278882
Analysis finished2022-12-14 19:30:11.708244
Duration36.43 seconds
Software versionpandas-profiling vv3.5.0
Download configurationconfig.json

Variables

gameId
Real number (ℝ)

Distinct24912
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5014795 × 109
Minimum4.3579703 × 109
Maximum4.5476715 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:11.801994image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum4.3579703 × 109
5-th percentile4.388642 × 109
Q14.4630514 × 109
median4.5293953 × 109
Q34.5437179 × 109
95-th percentile4.5469331 × 109
Maximum4.5476715 × 109
Range1.897012 × 108
Interquartile range (IQR)80666554

Descriptive statistics

Standard deviation53316928
Coefficient of variation (CV)0.011844312
Kurtosis-0.13090867
Mean4.5014795 × 109
Median Absolute Deviation (MAD)16933915
Skewness-1.0685572
Sum1.0919329 × 1015
Variance2.8426948 × 1015
MonotonicityNot monotonic
2022-12-14T20:30:11.927656image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4499508593 24
 
< 0.1%
4461394141 24
 
< 0.1%
4361896408 24
 
< 0.1%
4480555768 23
 
< 0.1%
4541995185 22
 
< 0.1%
4477562494 22
 
< 0.1%
4543730288 22
 
< 0.1%
4472654239 22
 
< 0.1%
4540065032 22
 
< 0.1%
4536425770 21
 
< 0.1%
Other values (24902) 242346
99.9%
ValueCountFrequency (%)
4357970300 13
< 0.1%
4357978575 9
< 0.1%
4358313595 8
< 0.1%
4358316661 6
< 0.1%
4358361767 9
< 0.1%
4358501352 10
< 0.1%
4358522445 8
< 0.1%
4358536899 8
< 0.1%
4358539887 5
 
< 0.1%
4358621881 12
< 0.1%
ValueCountFrequency (%)
4547671497 8
< 0.1%
4547662200 2
 
< 0.1%
4547601863 8
< 0.1%
4547584765 11
< 0.1%
4547584312 11
< 0.1%
4547581894 10
< 0.1%
4547581766 12
< 0.1%
4547579469 4
 
< 0.1%
4547579406 11
< 0.1%
4547575947 8
< 0.1%

gameDuration
Real number (ℝ)

Distinct2074
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1785493.9
Minimum549000
Maximum3428000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:12.064023image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum549000
5-th percentile1201000
Q11532000
median1774000
Q32025000
95-th percentile2433000
Maximum3428000
Range2879000
Interquartile range (IQR)493000

Descriptive statistics

Standard deviation376190.06
Coefficient of variation (CV)0.21069244
Kurtosis0.12736149
Mean1785493.9
Median Absolute Deviation (MAD)246000
Skewness0.20712283
Sum4.3311082 × 1011
Variance1.4151896 × 1011
MonotonicityNot monotonic
2022-12-14T20:30:12.196676image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1775000 495
 
0.2%
1750000 444
 
0.2%
1719000 430
 
0.2%
1779000 429
 
0.2%
1871000 428
 
0.2%
1776000 418
 
0.2%
2016000 416
 
0.2%
1720000 410
 
0.2%
1806000 407
 
0.2%
1778000 407
 
0.2%
Other values (2064) 238288
98.2%
ValueCountFrequency (%)
549000 1
< 0.1%
557000 1
< 0.1%
560000 1
< 0.1%
565000 1
< 0.1%
570000 2
< 0.1%
572000 1
< 0.1%
574000 2
< 0.1%
575000 1
< 0.1%
583000 1
< 0.1%
587000 1
< 0.1%
ValueCountFrequency (%)
3428000 24
< 0.1%
3345000 24
< 0.1%
3319000 24
< 0.1%
3268000 23
< 0.1%
3185000 22
< 0.1%
3177000 22
< 0.1%
3138000 22
< 0.1%
3125000 22
< 0.1%
3068000 22
< 0.1%
3062000 21
< 0.1%

hasWon
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
121740 
1
120832 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 121740
50.2%
1 120832
49.8%

Length

2022-12-14T20:30:12.318343image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:12.412708image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 121740
50.2%
1 120832
49.8%

Most occurring characters

ValueCountFrequency (%)
0 121740
50.2%
1 120832
49.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 121740
50.2%
1 120832
49.8%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 121740
50.2%
1 120832
49.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 121740
50.2%
1 120832
49.8%

frame
Real number (ℝ)

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.811264
Minimum10
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:12.494897image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10
Q114
median18
Q324
95-th percentile32
Maximum56
Range46
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.197339
Coefficient of variation (CV)0.36329529
Kurtosis-0.15763349
Mean19.811264
Median Absolute Deviation (MAD)6
Skewness0.60777214
Sum4805658
Variance51.801688
MonotonicityNot monotonic
2022-12-14T20:30:12.588646image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
10 24912
10.3%
12 24842
10.2%
14 24716
10.2%
16 24502
10.1%
18 23430
9.7%
20 22632
9.3%
22 20951
8.6%
24 18818
7.8%
26 16086
6.6%
28 12985
5.4%
Other values (14) 28698
11.8%
ValueCountFrequency (%)
10 24912
10.3%
12 24842
10.2%
14 24716
10.2%
16 24502
10.1%
18 23430
9.7%
20 22632
9.3%
22 20951
8.6%
24 18818
7.8%
26 16086
6.6%
28 12985
5.4%
ValueCountFrequency (%)
56 3
 
< 0.1%
54 4
 
< 0.1%
52 9
 
< 0.1%
50 25
 
< 0.1%
48 62
 
< 0.1%
46 132
 
0.1%
44 283
 
0.1%
42 557
 
0.2%
40 1013
0.4%
38 1838
0.8%

goldDiff
Real number (ℝ)

Distinct28629
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-11.413811
Minimum-21578
Maximum23432
Zeros20
Zeros (%)< 0.1%
Negative120776
Negative (%)49.8%
Memory size1.9 MiB
2022-12-14T20:30:12.700347image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-21578
5-th percentile-9277
Q1-3420.25
median24
Q33409
95-th percentile9126
Maximum23432
Range45010
Interquartile range (IQR)6829.25

Descriptive statistics

Standard deviation5438.0519
Coefficient of variation (CV)-476.44488
Kurtosis0.13085454
Mean-11.413811
Median Absolute Deviation (MAD)3414
Skewness-0.018917332
Sum-2768671
Variance29572409
MonotonicityNot monotonic
2022-12-14T20:30:12.819029image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
647 36
 
< 0.1%
-1199 35
 
< 0.1%
1248 35
 
< 0.1%
1634 34
 
< 0.1%
958 34
 
< 0.1%
278 34
 
< 0.1%
-1143 34
 
< 0.1%
425 33
 
< 0.1%
42 33
 
< 0.1%
2251 33
 
< 0.1%
Other values (28619) 242231
99.9%
ValueCountFrequency (%)
-21578 1
< 0.1%
-21314 1
< 0.1%
-21188 1
< 0.1%
-21173 1
< 0.1%
-21083 1
< 0.1%
-20993 1
< 0.1%
-20580 1
< 0.1%
-20470 1
< 0.1%
-20300 2
< 0.1%
-20220 1
< 0.1%
ValueCountFrequency (%)
23432 1
< 0.1%
22371 1
< 0.1%
22245 1
< 0.1%
22047 1
< 0.1%
22028 1
< 0.1%
21212 1
< 0.1%
20924 1
< 0.1%
20898 1
< 0.1%
20858 1
< 0.1%
20805 1
< 0.1%

expDiff
Real number (ℝ)

Distinct28949
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-215.01935
Minimum-32484
Maximum43304
Zeros29
Zeros (%)< 0.1%
Negative124261
Negative (%)51.2%
Memory size1.9 MiB
2022-12-14T20:30:12.941436image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-32484
5-th percentile-9367
Q1-3148
median-123
Q32772
95-th percentile8644
Maximum43304
Range75788
Interquartile range (IQR)5920

Descriptive statistics

Standard deviation5261.8808
Coefficient of variation (CV)-24.471662
Kurtosis0.75979282
Mean-215.01935
Median Absolute Deviation (MAD)2961
Skewness-0.067460243
Sum-52157674
Variance27687390
MonotonicityNot monotonic
2022-12-14T20:30:13.057149image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-589 42
 
< 0.1%
85 41
 
< 0.1%
-832 41
 
< 0.1%
-112 39
 
< 0.1%
1810 39
 
< 0.1%
-1713 39
 
< 0.1%
286 39
 
< 0.1%
480 39
 
< 0.1%
809 39
 
< 0.1%
705 39
 
< 0.1%
Other values (28939) 242175
99.8%
ValueCountFrequency (%)
-32484 1
< 0.1%
-31170 1
< 0.1%
-31032 1
< 0.1%
-30136 1
< 0.1%
-27737 1
< 0.1%
-27251 1
< 0.1%
-26310 1
< 0.1%
-25939 1
< 0.1%
-25807 1
< 0.1%
-25013 1
< 0.1%
ValueCountFrequency (%)
43304 1
< 0.1%
35253 1
< 0.1%
35028 1
< 0.1%
33909 1
< 0.1%
33836 1
< 0.1%
31012 1
< 0.1%
27384 1
< 0.1%
25867 1
< 0.1%
24334 1
< 0.1%
24307 1
< 0.1%

champLevelDiff
Real number (ℝ)

Distinct123
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.026516663
Minimum-4
Maximum3.8
Zeros26804
Zeros (%)11.0%
Negative110622
Negative (%)45.6%
Memory size1.9 MiB
2022-12-14T20:30:13.191767image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-4
5-th percentile-1.4
Q1-0.6
median0
Q30.4
95-th percentile1.2
Maximum3.8
Range7.8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.77236582
Coefficient of variation (CV)-29.127565
Kurtosis0.098705709
Mean-0.026516663
Median Absolute Deviation (MAD)0.4
Skewness-0.022812706
Sum-6432.2
Variance0.59654897
MonotonicityNot monotonic
2022-12-14T20:30:13.310125image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 26804
 
11.0%
-0.4 16835
 
6.9%
0.4 16467
 
6.8%
-0.6 12886
 
5.3%
0.6 12450
 
5.1%
0.2 11791
 
4.9%
-0.2 11754
 
4.8%
-1 10151
 
4.2%
1 9288
 
3.8%
-0.8 8008
 
3.3%
Other values (113) 106138
43.8%
ValueCountFrequency (%)
-4 1
 
< 0.1%
-3.8 1
 
< 0.1%
-3.6 1
 
< 0.1%
-3.6 1
 
< 0.1%
-3.4 1
 
< 0.1%
-3.4 1
 
< 0.1%
-3.2 7
 
< 0.1%
-3 7
 
< 0.1%
-3 2
 
< 0.1%
-2.8 23
< 0.1%
ValueCountFrequency (%)
3.8 1
 
< 0.1%
3.4 1
 
< 0.1%
3.2 4
 
< 0.1%
3 5
 
< 0.1%
2.8 12
 
< 0.1%
2.8 6
 
< 0.1%
2.8 5
 
< 0.1%
2.6 12
 
< 0.1%
2.6 6
 
< 0.1%
2.6 50
< 0.1%

isFirstTower
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
1
149839 
0
92733 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 149839
61.8%
0 92733
38.2%

Length

2022-12-14T20:30:13.531531image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:13.610322image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1 149839
61.8%
0 92733
38.2%

Most occurring characters

ValueCountFrequency (%)
1 149839
61.8%
0 92733
38.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 149839
61.8%
0 92733
38.2%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 149839
61.8%
0 92733
38.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 149839
61.8%
0 92733
38.2%

isFirstBlood
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
1
242239 
0
 
333

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 242239
99.9%
0 333
 
0.1%

Length

2022-12-14T20:30:13.678172image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:13.766833image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1 242239
99.9%
0 333
 
0.1%

Most occurring characters

ValueCountFrequency (%)
1 242239
99.9%
0 333
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 242239
99.9%
0 333
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 242239
99.9%
0 333
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 242239
99.9%
0 333
 
0.1%

killedFireDrake
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
176302 
1
61456 
2
 
4162
3
 
609
4
 
43

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 176302
72.7%
1 61456
 
25.3%
2 4162
 
1.7%
3 609
 
0.3%
4 43
 
< 0.1%

Length

2022-12-14T20:30:13.833654image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:13.915436image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 176302
72.7%
1 61456
 
25.3%
2 4162
 
1.7%
3 609
 
0.3%
4 43
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 176302
72.7%
1 61456
 
25.3%
2 4162
 
1.7%
3 609
 
0.3%
4 43
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 176302
72.7%
1 61456
 
25.3%
2 4162
 
1.7%
3 609
 
0.3%
4 43
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 176302
72.7%
1 61456
 
25.3%
2 4162
 
1.7%
3 609
 
0.3%
4 43
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 176302
72.7%
1 61456
 
25.3%
2 4162
 
1.7%
3 609
 
0.3%
4 43
 
< 0.1%

killedWaterDrake
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
175687 
1
61716 
2
 
4438
3
 
686
4
 
45

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 175687
72.4%
1 61716
 
25.4%
2 4438
 
1.8%
3 686
 
0.3%
4 45
 
< 0.1%

Length

2022-12-14T20:30:13.993228image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:14.087003image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 175687
72.4%
1 61716
 
25.4%
2 4438
 
1.8%
3 686
 
0.3%
4 45
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 175687
72.4%
1 61716
 
25.4%
2 4438
 
1.8%
3 686
 
0.3%
4 45
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 175687
72.4%
1 61716
 
25.4%
2 4438
 
1.8%
3 686
 
0.3%
4 45
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 175687
72.4%
1 61716
 
25.4%
2 4438
 
1.8%
3 686
 
0.3%
4 45
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 175687
72.4%
1 61716
 
25.4%
2 4438
 
1.8%
3 686
 
0.3%
4 45
 
< 0.1%

killedAirDrake
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
175258 
1
62132 
2
 
4480
3
 
657
4
 
45

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 175258
72.2%
1 62132
 
25.6%
2 4480
 
1.8%
3 657
 
0.3%
4 45
 
< 0.1%

Length

2022-12-14T20:30:14.167514image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:14.253081image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 175258
72.2%
1 62132
 
25.6%
2 4480
 
1.8%
3 657
 
0.3%
4 45
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 175258
72.2%
1 62132
 
25.6%
2 4480
 
1.8%
3 657
 
0.3%
4 45
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 175258
72.2%
1 62132
 
25.6%
2 4480
 
1.8%
3 657
 
0.3%
4 45
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 175258
72.2%
1 62132
 
25.6%
2 4480
 
1.8%
3 657
 
0.3%
4 45
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 175258
72.2%
1 62132
 
25.6%
2 4480
 
1.8%
3 657
 
0.3%
4 45
 
< 0.1%

killedEarthDrake
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
175179 
1
61951 
2
 
4665
3
 
742
4
 
35

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 175179
72.2%
1 61951
 
25.5%
2 4665
 
1.9%
3 742
 
0.3%
4 35
 
< 0.1%

Length

2022-12-14T20:30:14.330871image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:14.418648image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 175179
72.2%
1 61951
 
25.5%
2 4665
 
1.9%
3 742
 
0.3%
4 35
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 175179
72.2%
1 61951
 
25.5%
2 4665
 
1.9%
3 742
 
0.3%
4 35
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 175179
72.2%
1 61951
 
25.5%
2 4665
 
1.9%
3 742
 
0.3%
4 35
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 175179
72.2%
1 61951
 
25.5%
2 4665
 
1.9%
3 742
 
0.3%
4 35
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 175179
72.2%
1 61951
 
25.5%
2 4665
 
1.9%
3 742
 
0.3%
4 35
 
< 0.1%

killedElderDrake
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
241295 
1
 
1212
2
 
62
3
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 241295
99.5%
1 1212
 
0.5%
2 62
 
< 0.1%
3 3
 
< 0.1%

Length

2022-12-14T20:30:14.496429image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:14.586188image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 241295
99.5%
1 1212
 
0.5%
2 62
 
< 0.1%
3 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 241295
99.5%
1 1212
 
0.5%
2 62
 
< 0.1%
3 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 241295
99.5%
1 1212
 
0.5%
2 62
 
< 0.1%
3 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 241295
99.5%
1 1212
 
0.5%
2 62
 
< 0.1%
3 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 241295
99.5%
1 1212
 
0.5%
2 62
 
< 0.1%
3 3
 
< 0.1%

lostFireDrake
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
173628 
1
63871 
2
 
4281
3
 
758
4
 
34

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 173628
71.6%
1 63871
 
26.3%
2 4281
 
1.8%
3 758
 
0.3%
4 34
 
< 0.1%

Length

2022-12-14T20:30:14.661985image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:14.749775image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 173628
71.6%
1 63871
 
26.3%
2 4281
 
1.8%
3 758
 
0.3%
4 34
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 173628
71.6%
1 63871
 
26.3%
2 4281
 
1.8%
3 758
 
0.3%
4 34
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 173628
71.6%
1 63871
 
26.3%
2 4281
 
1.8%
3 758
 
0.3%
4 34
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 173628
71.6%
1 63871
 
26.3%
2 4281
 
1.8%
3 758
 
0.3%
4 34
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 173628
71.6%
1 63871
 
26.3%
2 4281
 
1.8%
3 758
 
0.3%
4 34
 
< 0.1%

lostWaterDrake
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
172663 
1
64493 
2
 
4633
3
 
748
4
 
35

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 172663
71.2%
1 64493
 
26.6%
2 4633
 
1.9%
3 748
 
0.3%
4 35
 
< 0.1%

Length

2022-12-14T20:30:14.829538image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:14.916060image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 172663
71.2%
1 64493
 
26.6%
2 4633
 
1.9%
3 748
 
0.3%
4 35
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 172663
71.2%
1 64493
 
26.6%
2 4633
 
1.9%
3 748
 
0.3%
4 35
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 172663
71.2%
1 64493
 
26.6%
2 4633
 
1.9%
3 748
 
0.3%
4 35
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 172663
71.2%
1 64493
 
26.6%
2 4633
 
1.9%
3 748
 
0.3%
4 35
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 172663
71.2%
1 64493
 
26.6%
2 4633
 
1.9%
3 748
 
0.3%
4 35
 
< 0.1%

lostAirDrake
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
172413 
1
64722 
2
 
4629
3
 
769
4
 
39

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 172413
71.1%
1 64722
 
26.7%
2 4629
 
1.9%
3 769
 
0.3%
4 39
 
< 0.1%

Length

2022-12-14T20:30:14.999809image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:15.111508image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 172413
71.1%
1 64722
 
26.7%
2 4629
 
1.9%
3 769
 
0.3%
4 39
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 172413
71.1%
1 64722
 
26.7%
2 4629
 
1.9%
3 769
 
0.3%
4 39
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 172413
71.1%
1 64722
 
26.7%
2 4629
 
1.9%
3 769
 
0.3%
4 39
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 172413
71.1%
1 64722
 
26.7%
2 4629
 
1.9%
3 769
 
0.3%
4 39
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 172413
71.1%
1 64722
 
26.7%
2 4629
 
1.9%
3 769
 
0.3%
4 39
 
< 0.1%

lostEarthDrake
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
171848 
1
64861 
2
 
4915
3
 
910
4
 
38

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 171848
70.8%
1 64861
 
26.7%
2 4915
 
2.0%
3 910
 
0.4%
4 38
 
< 0.1%

Length

2022-12-14T20:30:15.196280image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:15.284047image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 171848
70.8%
1 64861
 
26.7%
2 4915
 
2.0%
3 910
 
0.4%
4 38
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 171848
70.8%
1 64861
 
26.7%
2 4915
 
2.0%
3 910
 
0.4%
4 38
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 171848
70.8%
1 64861
 
26.7%
2 4915
 
2.0%
3 910
 
0.4%
4 38
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 171848
70.8%
1 64861
 
26.7%
2 4915
 
2.0%
3 910
 
0.4%
4 38
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 171848
70.8%
1 64861
 
26.7%
2 4915
 
2.0%
3 910
 
0.4%
4 38
 
< 0.1%

lostElderDrake
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
241254 
1
 
1253
2
 
62
3
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 241254
99.5%
1 1253
 
0.5%
2 62
 
< 0.1%
3 3
 
< 0.1%

Length

2022-12-14T20:30:15.366826image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:15.447609image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 241254
99.5%
1 1253
 
0.5%
2 62
 
< 0.1%
3 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 241254
99.5%
1 1253
 
0.5%
2 62
 
< 0.1%
3 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 241254
99.5%
1 1253
 
0.5%
2 62
 
< 0.1%
3 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 241254
99.5%
1 1253
 
0.5%
2 62
 
< 0.1%
3 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 241254
99.5%
1 1253
 
0.5%
2 62
 
< 0.1%
3 3
 
< 0.1%

killedBaronNashor
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
211716 
1
27613 
2
 
3076
3
 
164
4
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 211716
87.3%
1 27613
 
11.4%
2 3076
 
1.3%
3 164
 
0.1%
4 3
 
< 0.1%

Length

2022-12-14T20:30:15.521410image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:15.612169image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 211716
87.3%
1 27613
 
11.4%
2 3076
 
1.3%
3 164
 
0.1%
4 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 211716
87.3%
1 27613
 
11.4%
2 3076
 
1.3%
3 164
 
0.1%
4 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 211716
87.3%
1 27613
 
11.4%
2 3076
 
1.3%
3 164
 
0.1%
4 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 211716
87.3%
1 27613
 
11.4%
2 3076
 
1.3%
3 164
 
0.1%
4 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 211716
87.3%
1 27613
 
11.4%
2 3076
 
1.3%
3 164
 
0.1%
4 3
 
< 0.1%

lostBaronNashor
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
208434 
1
30087 
2
 
3842
3
 
204
4
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 208434
85.9%
1 30087
 
12.4%
2 3842
 
1.6%
3 204
 
0.1%
4 5
 
< 0.1%

Length

2022-12-14T20:30:15.691956image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:15.773735image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 208434
85.9%
1 30087
 
12.4%
2 3842
 
1.6%
3 204
 
0.1%
4 5
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 208434
85.9%
1 30087
 
12.4%
2 3842
 
1.6%
3 204
 
0.1%
4 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 208434
85.9%
1 30087
 
12.4%
2 3842
 
1.6%
3 204
 
0.1%
4 5
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 208434
85.9%
1 30087
 
12.4%
2 3842
 
1.6%
3 204
 
0.1%
4 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 208434
85.9%
1 30087
 
12.4%
2 3842
 
1.6%
3 204
 
0.1%
4 5
 
< 0.1%

killedRiftHerald
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
129581 
1
89094 
2
23897 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 129581
53.4%
1 89094
36.7%
2 23897
 
9.9%

Length

2022-12-14T20:30:15.861251image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:15.945001image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 129581
53.4%
1 89094
36.7%
2 23897
 
9.9%

Most occurring characters

ValueCountFrequency (%)
0 129581
53.4%
1 89094
36.7%
2 23897
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 129581
53.4%
1 89094
36.7%
2 23897
 
9.9%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 129581
53.4%
1 89094
36.7%
2 23897
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 129581
53.4%
1 89094
36.7%
2 23897
 
9.9%

lostRiftHerald
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
122563 
1
90259 
2
29750 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 122563
50.5%
1 90259
37.2%
2 29750
 
12.3%

Length

2022-12-14T20:30:16.023791image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:16.110574image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 122563
50.5%
1 90259
37.2%
2 29750
 
12.3%

Most occurring characters

ValueCountFrequency (%)
0 122563
50.5%
1 90259
37.2%
2 29750
 
12.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 122563
50.5%
1 90259
37.2%
2 29750
 
12.3%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 122563
50.5%
1 90259
37.2%
2 29750
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 122563
50.5%
1 90259
37.2%
2 29750
 
12.3%

destroyedTopInhibitor
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
237522 
1
 
4787
2
 
245
3
 
18

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 237522
97.9%
1 4787
 
2.0%
2 245
 
0.1%
3 18
 
< 0.1%

Length

2022-12-14T20:30:16.194162image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:16.281927image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 237522
97.9%
1 4787
 
2.0%
2 245
 
0.1%
3 18
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 237522
97.9%
1 4787
 
2.0%
2 245
 
0.1%
3 18
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 237522
97.9%
1 4787
 
2.0%
2 245
 
0.1%
3 18
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 237522
97.9%
1 4787
 
2.0%
2 245
 
0.1%
3 18
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 237522
97.9%
1 4787
 
2.0%
2 245
 
0.1%
3 18
 
< 0.1%

destroyedMidInhibitor
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
235660 
1
 
6548
2
 
352
3
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 235660
97.2%
1 6548
 
2.7%
2 352
 
0.1%
3 12
 
< 0.1%

Length

2022-12-14T20:30:16.358720image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:16.444490image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 235660
97.2%
1 6548
 
2.7%
2 352
 
0.1%
3 12
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 235660
97.2%
1 6548
 
2.7%
2 352
 
0.1%
3 12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 235660
97.2%
1 6548
 
2.7%
2 352
 
0.1%
3 12
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 235660
97.2%
1 6548
 
2.7%
2 352
 
0.1%
3 12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 235660
97.2%
1 6548
 
2.7%
2 352
 
0.1%
3 12
 
< 0.1%

destroyedBotInhibitor
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
223352 
1
 
17312
2
 
1775
3
 
123
4
 
10

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 223352
92.1%
1 17312
 
7.1%
2 1775
 
0.7%
3 123
 
0.1%
4 10
 
< 0.1%

Length

2022-12-14T20:30:16.517297image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:16.734419image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 223352
92.1%
1 17312
 
7.1%
2 1775
 
0.7%
3 123
 
0.1%
4 10
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 223352
92.1%
1 17312
 
7.1%
2 1775
 
0.7%
3 123
 
0.1%
4 10
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 223352
92.1%
1 17312
 
7.1%
2 1775
 
0.7%
3 123
 
0.1%
4 10
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 223352
92.1%
1 17312
 
7.1%
2 1775
 
0.7%
3 123
 
0.1%
4 10
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 223352
92.1%
1 17312
 
7.1%
2 1775
 
0.7%
3 123
 
0.1%
4 10
 
< 0.1%

lostTopInhibitor
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
237522 
1
 
4786
2
 
251
3
 
13

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 237522
97.9%
1 4786
 
2.0%
2 251
 
0.1%
3 13
 
< 0.1%

Length

2022-12-14T20:30:16.812208image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:16.905529image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 237522
97.9%
1 4786
 
2.0%
2 251
 
0.1%
3 13
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 237522
97.9%
1 4786
 
2.0%
2 251
 
0.1%
3 13
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 237522
97.9%
1 4786
 
2.0%
2 251
 
0.1%
3 13
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 237522
97.9%
1 4786
 
2.0%
2 251
 
0.1%
3 13
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 237522
97.9%
1 4786
 
2.0%
2 251
 
0.1%
3 13
 
< 0.1%

lostMidInhibitor
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
235594 
1
 
6604
2
 
363
3
 
11

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 235594
97.1%
1 6604
 
2.7%
2 363
 
0.1%
3 11
 
< 0.1%

Length

2022-12-14T20:30:16.995289image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:17.089039image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 235594
97.1%
1 6604
 
2.7%
2 363
 
0.1%
3 11
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 235594
97.1%
1 6604
 
2.7%
2 363
 
0.1%
3 11
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 235594
97.1%
1 6604
 
2.7%
2 363
 
0.1%
3 11
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 235594
97.1%
1 6604
 
2.7%
2 363
 
0.1%
3 11
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 235594
97.1%
1 6604
 
2.7%
2 363
 
0.1%
3 11
 
< 0.1%

lostBotInhibitor
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
224474 
1
 
16536
2
 
1474
3
 
86
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 224474
92.5%
1 16536
 
6.8%
2 1474
 
0.6%
3 86
 
< 0.1%
4 2
 
< 0.1%

Length

2022-12-14T20:30:17.164834image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:17.255593image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 224474
92.5%
1 16536
 
6.8%
2 1474
 
0.6%
3 86
 
< 0.1%
4 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 224474
92.5%
1 16536
 
6.8%
2 1474
 
0.6%
3 86
 
< 0.1%
4 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 224474
92.5%
1 16536
 
6.8%
2 1474
 
0.6%
3 86
 
< 0.1%
4 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 224474
92.5%
1 16536
 
6.8%
2 1474
 
0.6%
3 86
 
< 0.1%
4 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 224474
92.5%
1 16536
 
6.8%
2 1474
 
0.6%
3 86
 
< 0.1%
4 2
 
< 0.1%

destroyedTopNexusTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
234765 
1
 
7807

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 234765
96.8%
1 7807
 
3.2%

Length

2022-12-14T20:30:17.334380image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:17.419156image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 234765
96.8%
1 7807
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 234765
96.8%
1 7807
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 234765
96.8%
1 7807
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 234765
96.8%
1 7807
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 234765
96.8%
1 7807
 
3.2%

destroyedMidNexusTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
233173 
1
 
9399

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 233173
96.1%
1 9399
 
3.9%

Length

2022-12-14T20:30:17.489611image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:17.576110image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 233173
96.1%
1 9399
 
3.9%

Most occurring characters

ValueCountFrequency (%)
0 233173
96.1%
1 9399
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 233173
96.1%
1 9399
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 233173
96.1%
1 9399
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 233173
96.1%
1 9399
 
3.9%

destroyedBotNexusTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
217913 
1
24659 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 217913
89.8%
1 24659
 
10.2%

Length

2022-12-14T20:30:17.645923image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:17.728703image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 217913
89.8%
1 24659
 
10.2%

Most occurring characters

ValueCountFrequency (%)
0 217913
89.8%
1 24659
 
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 217913
89.8%
1 24659
 
10.2%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 217913
89.8%
1 24659
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 217913
89.8%
1 24659
 
10.2%

lostTopNexusTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
235192 
1
 
7380

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 235192
97.0%
1 7380
 
3.0%

Length

2022-12-14T20:30:17.797518image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:17.884286image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 235192
97.0%
1 7380
 
3.0%

Most occurring characters

ValueCountFrequency (%)
0 235192
97.0%
1 7380
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 235192
97.0%
1 7380
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 235192
97.0%
1 7380
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 235192
97.0%
1 7380
 
3.0%

lostMidNexusTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
233396 
1
 
9176

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 233396
96.2%
1 9176
 
3.8%

Length

2022-12-14T20:30:17.951136image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:18.030893image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 233396
96.2%
1 9176
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 233396
96.2%
1 9176
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 233396
96.2%
1 9176
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 233396
96.2%
1 9176
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 233396
96.2%
1 9176
 
3.8%

lostBotNexusTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
219968 
1
22604 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 219968
90.7%
1 22604
 
9.3%

Length

2022-12-14T20:30:18.101703image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:18.185480image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 219968
90.7%
1 22604
 
9.3%

Most occurring characters

ValueCountFrequency (%)
0 219968
90.7%
1 22604
 
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 219968
90.7%
1 22604
 
9.3%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 219968
90.7%
1 22604
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 219968
90.7%
1 22604
 
9.3%

destroyedTopBaseTurret
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
242572 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 242572
100.0%

Length

2022-12-14T20:30:18.259282image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:18.340067image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 242572
100.0%

Most occurring characters

ValueCountFrequency (%)
0 242572
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 242572
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 242572
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 242572
100.0%

destroyedMidBaseTurret
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
242572 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 242572
100.0%

Length

2022-12-14T20:30:18.405891image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:18.482684image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 242572
100.0%

Most occurring characters

ValueCountFrequency (%)
0 242572
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 242572
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 242572
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 242572
100.0%

destroyedBotBaseTurret
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
233795 
1
 
4939
2
 
3838

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 233795
96.4%
1 4939
 
2.0%
2 3838
 
1.6%

Length

2022-12-14T20:30:18.548509image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:18.634280image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 233795
96.4%
1 4939
 
2.0%
2 3838
 
1.6%

Most occurring characters

ValueCountFrequency (%)
0 233795
96.4%
1 4939
 
2.0%
2 3838
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 233795
96.4%
1 4939
 
2.0%
2 3838
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 233795
96.4%
1 4939
 
2.0%
2 3838
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 233795
96.4%
1 4939
 
2.0%
2 3838
 
1.6%

lostTopBaseTurret
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
242572 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 242572
100.0%

Length

2022-12-14T20:30:18.708081image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:18.783878image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 242572
100.0%

Most occurring characters

ValueCountFrequency (%)
0 242572
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 242572
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 242572
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 242572
100.0%

lostMidBaseTurret
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
242572 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 242572
100.0%

Length

2022-12-14T20:30:18.850700image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:18.932482image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 242572
100.0%

Most occurring characters

ValueCountFrequency (%)
0 242572
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 242572
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 242572
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 242572
100.0%

lostBotBaseTurret
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
234099 
1
 
4574
2
 
3899

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 234099
96.5%
1 4574
 
1.9%
2 3899
 
1.6%

Length

2022-12-14T20:30:19.001009image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:19.087776image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 234099
96.5%
1 4574
 
1.9%
2 3899
 
1.6%

Most occurring characters

ValueCountFrequency (%)
0 234099
96.5%
1 4574
 
1.9%
2 3899
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 234099
96.5%
1 4574
 
1.9%
2 3899
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 234099
96.5%
1 4574
 
1.9%
2 3899
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 234099
96.5%
1 4574
 
1.9%
2 3899
 
1.6%

destroyedTopInnerTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
213312 
1
29260 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 213312
87.9%
1 29260
 
12.1%

Length

2022-12-14T20:30:19.161579image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:19.246353image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 213312
87.9%
1 29260
 
12.1%

Most occurring characters

ValueCountFrequency (%)
0 213312
87.9%
1 29260
 
12.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 213312
87.9%
1 29260
 
12.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 213312
87.9%
1 29260
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 213312
87.9%
1 29260
 
12.1%

destroyedMidInnerTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
214117 
1
28455 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 214117
88.3%
1 28455
 
11.7%

Length

2022-12-14T20:30:19.321153image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:19.400938image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 214117
88.3%
1 28455
 
11.7%

Most occurring characters

ValueCountFrequency (%)
0 214117
88.3%
1 28455
 
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 214117
88.3%
1 28455
 
11.7%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 214117
88.3%
1 28455
 
11.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 214117
88.3%
1 28455
 
11.7%

destroyedBotInnerTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
195749 
1
46823 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 195749
80.7%
1 46823
 
19.3%

Length

2022-12-14T20:30:19.469754image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:19.548543image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 195749
80.7%
1 46823
 
19.3%

Most occurring characters

ValueCountFrequency (%)
0 195749
80.7%
1 46823
 
19.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 195749
80.7%
1 46823
 
19.3%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 195749
80.7%
1 46823
 
19.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 195749
80.7%
1 46823
 
19.3%

lostTopInnerTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
215647 
1
26925 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 215647
88.9%
1 26925
 
11.1%

Length

2022-12-14T20:30:19.623343image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:19.706123image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 215647
88.9%
1 26925
 
11.1%

Most occurring characters

ValueCountFrequency (%)
0 215647
88.9%
1 26925
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 215647
88.9%
1 26925
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 215647
88.9%
1 26925
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 215647
88.9%
1 26925
 
11.1%

lostMidInnerTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
214057 
1
28515 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 214057
88.2%
1 28515
 
11.8%

Length

2022-12-14T20:30:19.782590image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:19.866366image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 214057
88.2%
1 28515
 
11.8%

Most occurring characters

ValueCountFrequency (%)
0 214057
88.2%
1 28515
 
11.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 214057
88.2%
1 28515
 
11.8%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 214057
88.2%
1 28515
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 214057
88.2%
1 28515
 
11.8%

lostBotInnerTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
199096 
1
43476 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 199096
82.1%
1 43476
 
17.9%

Length

2022-12-14T20:30:19.942163image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:20.038904image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 199096
82.1%
1 43476
 
17.9%

Most occurring characters

ValueCountFrequency (%)
0 199096
82.1%
1 43476
 
17.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 199096
82.1%
1 43476
 
17.9%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 199096
82.1%
1 43476
 
17.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 199096
82.1%
1 43476
 
17.9%

destroyedTopOuterTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
150519 
1
92053 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 150519
62.1%
1 92053
37.9%

Length

2022-12-14T20:30:20.112707image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:20.199475image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 150519
62.1%
1 92053
37.9%

Most occurring characters

ValueCountFrequency (%)
0 150519
62.1%
1 92053
37.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 150519
62.1%
1 92053
37.9%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 150519
62.1%
1 92053
37.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 150519
62.1%
1 92053
37.9%

destroyedMidOuterTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
149941 
1
92631 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 149941
61.8%
1 92631
38.2%

Length

2022-12-14T20:30:20.277047image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:20.356835image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 149941
61.8%
1 92631
38.2%

Most occurring characters

ValueCountFrequency (%)
0 149941
61.8%
1 92631
38.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 149941
61.8%
1 92631
38.2%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 149941
61.8%
1 92631
38.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 149941
61.8%
1 92631
38.2%

destroyedBotOuterTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
152821 
1
89751 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 152821
63.0%
1 89751
37.0%

Length

2022-12-14T20:30:20.424653image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:20.673486image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 152821
63.0%
1 89751
37.0%

Most occurring characters

ValueCountFrequency (%)
0 152821
63.0%
1 89751
37.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 152821
63.0%
1 89751
37.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 152821
63.0%
1 89751
37.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 152821
63.0%
1 89751
37.0%

lostTopOuterTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
151172 
1
91400 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 151172
62.3%
1 91400
37.7%

Length

2022-12-14T20:30:20.741306image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:20.821091image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 151172
62.3%
1 91400
37.7%

Most occurring characters

ValueCountFrequency (%)
0 151172
62.3%
1 91400
37.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 151172
62.3%
1 91400
37.7%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 151172
62.3%
1 91400
37.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 151172
62.3%
1 91400
37.7%

lostMidOuterTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
153106 
1
89466 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 153106
63.1%
1 89466
36.9%

Length

2022-12-14T20:30:20.889610image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:20.966404image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 153106
63.1%
1 89466
36.9%

Most occurring characters

ValueCountFrequency (%)
0 153106
63.1%
1 89466
36.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 153106
63.1%
1 89466
36.9%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 153106
63.1%
1 89466
36.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 153106
63.1%
1 89466
36.9%

lostBotOuterTurret
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
156400 
1
86172 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 156400
64.5%
1 86172
35.5%

Length

2022-12-14T20:30:21.035219image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:21.113011image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 156400
64.5%
1 86172
35.5%

Most occurring characters

ValueCountFrequency (%)
0 156400
64.5%
1 86172
35.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 156400
64.5%
1 86172
35.5%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 156400
64.5%
1 86172
35.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 156400
64.5%
1 86172
35.5%

kills
Real number (ℝ)

Distinct70
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.391381
Minimum0
Maximum69
Zeros333
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:21.196788image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q19
median15
Q322
95-th percentile35
Maximum69
Range69
Interquartile range (IQR)13

Descriptive statistics

Standard deviation9.6602366
Coefficient of variation (CV)0.58934856
Kurtosis0.28289625
Mean16.391381
Median Absolute Deviation (MAD)7
Skewness0.79895137
Sum3976090
Variance93.320171
MonotonicityNot monotonic
2022-12-14T20:30:21.309545image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 11397
 
4.7%
8 11199
 
4.6%
10 11176
 
4.6%
11 10781
 
4.4%
7 10780
 
4.4%
12 10432
 
4.3%
13 10016
 
4.1%
6 10005
 
4.1%
14 9680
 
4.0%
15 9169
 
3.8%
Other values (60) 137937
56.9%
ValueCountFrequency (%)
0 333
 
0.1%
1 1340
 
0.6%
2 2950
 
1.2%
3 4739
2.0%
4 6938
2.9%
5 8693
3.6%
6 10005
4.1%
7 10780
4.4%
8 11199
4.6%
9 11397
4.7%
ValueCountFrequency (%)
69 1
 
< 0.1%
68 1
 
< 0.1%
67 1
 
< 0.1%
66 2
 
< 0.1%
65 2
 
< 0.1%
64 3
< 0.1%
63 2
 
< 0.1%
62 7
< 0.1%
61 5
< 0.1%
60 7
< 0.1%

deaths
Real number (ℝ)

Distinct70
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.34222
Minimum0
Maximum72
Zeros402
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:21.430222image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q19
median15
Q322
95-th percentile35
Maximum72
Range72
Interquartile range (IQR)13

Descriptive statistics

Standard deviation9.6976016
Coefficient of variation (CV)0.59340785
Kurtosis0.29378364
Mean16.34222
Median Absolute Deviation (MAD)7
Skewness0.80385283
Sum3964165
Variance94.043477
MonotonicityNot monotonic
2022-12-14T20:30:21.542920image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 11325
 
4.7%
8 11104
 
4.6%
10 11046
 
4.6%
7 10954
 
4.5%
11 10790
 
4.4%
12 10579
 
4.4%
6 10010
 
4.1%
13 9943
 
4.1%
14 9617
 
4.0%
15 9292
 
3.8%
Other values (60) 137912
56.9%
ValueCountFrequency (%)
0 402
 
0.2%
1 1390
 
0.6%
2 3075
 
1.3%
3 5062
2.1%
4 7071
2.9%
5 8749
3.6%
6 10010
4.1%
7 10954
4.5%
8 11104
4.6%
9 11325
4.7%
ValueCountFrequency (%)
72 1
 
< 0.1%
71 1
 
< 0.1%
68 1
 
< 0.1%
67 2
 
< 0.1%
65 1
 
< 0.1%
64 4
< 0.1%
63 3
 
< 0.1%
62 9
< 0.1%
61 4
< 0.1%
60 8
< 0.1%

assists
Real number (ℝ)

Distinct122
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.166029
Minimum0
Maximum137
Zeros1361
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:21.658612image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q19
median17
Q330
95-th percentile53
Maximum137
Range137
Interquartile range (IQR)21

Descriptive statistics

Standard deviation16.055645
Coefficient of variation (CV)0.75855725
Kurtosis1.4506861
Mean21.166029
Median Absolute Deviation (MAD)9
Skewness1.2132019
Sum5134286
Variance257.78373
MonotonicityNot monotonic
2022-12-14T20:30:21.765981image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 9038
 
3.7%
9 9003
 
3.7%
7 8999
 
3.7%
6 8634
 
3.6%
10 8580
 
3.5%
11 8214
 
3.4%
5 8110
 
3.3%
12 7987
 
3.3%
13 7651
 
3.2%
4 7364
 
3.0%
Other values (112) 158992
65.5%
ValueCountFrequency (%)
0 1361
 
0.6%
1 2944
 
1.2%
2 4558
1.9%
3 5972
2.5%
4 7364
3.0%
5 8110
3.3%
6 8634
3.6%
7 8999
3.7%
8 9038
3.7%
9 9003
3.7%
ValueCountFrequency (%)
137 1
 
< 0.1%
127 1
 
< 0.1%
126 1
 
< 0.1%
119 2
< 0.1%
117 1
 
< 0.1%
116 2
< 0.1%
115 2
< 0.1%
114 4
< 0.1%
113 1
 
< 0.1%
112 4
< 0.1%

wardsPlaced
Real number (ℝ)

Distinct663
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.83353
Minimum3
Maximum1014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:21.885660image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile14
Q125
median40
Q363
95-th percentile167
Maximum1014
Range1011
Interquartile range (IQR)38

Descriptive statistics

Standard deviation58.734777
Coefficient of variation (CV)1.0334529
Kurtosis20.095967
Mean56.83353
Median Absolute Deviation (MAD)18
Skewness3.709929
Sum13786223
Variance3449.774
MonotonicityNot monotonic
2022-12-14T20:30:22.022176image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17 4924
 
2.0%
16 4916
 
2.0%
18 4876
 
2.0%
15 4789
 
2.0%
19 4778
 
2.0%
21 4672
 
1.9%
20 4618
 
1.9%
22 4522
 
1.9%
23 4515
 
1.9%
24 4344
 
1.8%
Other values (653) 195618
80.6%
ValueCountFrequency (%)
3 3
 
< 0.1%
4 4
 
< 0.1%
5 8
 
< 0.1%
6 17
 
< 0.1%
7 56
 
< 0.1%
8 135
 
0.1%
9 306
 
0.1%
10 735
 
0.3%
11 1337
0.6%
12 2220
0.9%
ValueCountFrequency (%)
1014 1
< 0.1%
945 1
< 0.1%
913 1
< 0.1%
904 1
< 0.1%
886 1
< 0.1%
870 1
< 0.1%
859 1
< 0.1%
847 1
< 0.1%
834 1
< 0.1%
832 1
< 0.1%

wardsDestroyed
Real number (ℝ)

Distinct103
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.487031
Minimum0
Maximum115
Zeros5013
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:22.157812image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median8
Q315
95-th percentile27
Maximum115
Range115
Interquartile range (IQR)11

Descriptive statistics

Standard deviation8.7135485
Coefficient of variation (CV)0.83088806
Kurtosis5.9967801
Mean10.487031
Median Absolute Deviation (MAD)5
Skewness1.7925849
Sum2543860
Variance75.925928
MonotonicityNot monotonic
2022-12-14T20:30:22.286469image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 17635
 
7.3%
4 16791
 
6.9%
2 16252
 
6.7%
5 15567
 
6.4%
6 14757
 
6.1%
7 13355
 
5.5%
8 12549
 
5.2%
1 11885
 
4.9%
9 11668
 
4.8%
10 10876
 
4.5%
Other values (93) 101237
41.7%
ValueCountFrequency (%)
0 5013
 
2.1%
1 11885
4.9%
2 16252
6.7%
3 17635
7.3%
4 16791
6.9%
5 15567
6.4%
6 14757
6.1%
7 13355
5.5%
8 12549
5.2%
9 11668
4.8%
ValueCountFrequency (%)
115 1
 
< 0.1%
109 1
 
< 0.1%
107 1
 
< 0.1%
105 2
 
< 0.1%
102 1
 
< 0.1%
99 2
 
< 0.1%
97 3
< 0.1%
96 2
 
< 0.1%
94 3
< 0.1%
93 5
< 0.1%

wardsLost
Real number (ℝ)

Distinct101
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.263077
Minimum0
Maximum107
Zeros5548
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:22.414127image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median8
Q314
95-th percentile27
Maximum107
Range107
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.736323
Coefficient of variation (CV)0.85123822
Kurtosis6.5816951
Mean10.263077
Median Absolute Deviation (MAD)5
Skewness1.8895257
Sum2489535
Variance76.323339
MonotonicityNot monotonic
2022-12-14T20:30:22.535802image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 18040
 
7.4%
2 17206
 
7.1%
4 17041
 
7.0%
5 15903
 
6.6%
6 14515
 
6.0%
7 13510
 
5.6%
1 13003
 
5.4%
8 12435
 
5.1%
9 11598
 
4.8%
10 10489
 
4.3%
Other values (91) 98832
40.7%
ValueCountFrequency (%)
0 5548
 
2.3%
1 13003
5.4%
2 17206
7.1%
3 18040
7.4%
4 17041
7.0%
5 15903
6.6%
6 14515
6.0%
7 13510
5.6%
8 12435
5.1%
9 11598
4.8%
ValueCountFrequency (%)
107 1
 
< 0.1%
102 1
 
< 0.1%
100 1
 
< 0.1%
99 1
 
< 0.1%
97 1
 
< 0.1%
96 4
< 0.1%
95 2
< 0.1%
94 3
< 0.1%
93 3
< 0.1%
91 2
< 0.1%

KDA
Real number (ℝ)

Distinct3508
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6802626
Minimum0
Maximum67
Zeros333
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:22.656478image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.75
Q11.5
median2.2352941
Q33.25
95-th percentile5.9
Maximum67
Range67
Interquartile range (IQR)1.75

Descriptive statistics

Standard deviation2.0950452
Coefficient of variation (CV)0.7816567
Kurtosis56.319365
Mean2.6802626
Median Absolute Deviation (MAD)0.83529412
Skewness5.0089506
Sum650156.66
Variance4.3892145
MonotonicityNot monotonic
2022-12-14T20:30:22.773167image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 6254
 
2.6%
1 4552
 
1.9%
3 4476
 
1.8%
1.5 3004
 
1.2%
4 2807
 
1.2%
2.5 2674
 
1.1%
1.666666667 2073
 
0.9%
2.333333333 1916
 
0.8%
1.333333333 1845
 
0.8%
2.666666667 1780
 
0.7%
Other values (3498) 211191
87.1%
ValueCountFrequency (%)
0 333
0.1%
0.04 1
 
< 0.1%
0.04761904762 1
 
< 0.1%
0.05 1
 
< 0.1%
0.05263157895 1
 
< 0.1%
0.05555555556 1
 
< 0.1%
0.05882352941 1
 
< 0.1%
0.0625 4
 
< 0.1%
0.06666666667 3
 
< 0.1%
0.07142857143 5
 
< 0.1%
ValueCountFrequency (%)
67 1
 
< 0.1%
57 1
 
< 0.1%
53 1
 
< 0.1%
51 2
< 0.1%
50 4
< 0.1%
47 2
< 0.1%
45 2
< 0.1%
44 1
 
< 0.1%
43 3
< 0.1%
42 4
< 0.1%

visionScore
Real number (ℝ)

Distinct671
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.32056
Minimum3
Maximum1037
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:22.894524image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile17
Q130
median50
Q380
95-th percentile183
Maximum1037
Range1034
Interquartile range (IQR)50

Descriptive statistics

Standard deviation62.401838
Coefficient of variation (CV)0.9269358
Kurtosis16.993572
Mean67.32056
Median Absolute Deviation (MAD)23
Skewness3.3203317
Sum16330083
Variance3893.9894
MonotonicityNot monotonic
2022-12-14T20:30:23.011006image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 3831
 
1.6%
19 3768
 
1.6%
21 3727
 
1.5%
18 3699
 
1.5%
22 3681
 
1.5%
17 3665
 
1.5%
23 3636
 
1.5%
24 3503
 
1.4%
25 3500
 
1.4%
26 3460
 
1.4%
Other values (661) 206102
85.0%
ValueCountFrequency (%)
3 3
 
< 0.1%
4 3
 
< 0.1%
5 6
 
< 0.1%
6 13
 
< 0.1%
7 20
 
< 0.1%
8 46
 
< 0.1%
9 143
 
0.1%
10 278
 
0.1%
11 548
0.2%
12 961
0.4%
ValueCountFrequency (%)
1037 1
< 0.1%
965 1
< 0.1%
942 1
< 0.1%
927 1
< 0.1%
905 1
< 0.1%
897 1
< 0.1%
894 1
< 0.1%
869 1
< 0.1%
859 1
< 0.1%
852 1
< 0.1%

improvedVisionScore
Real number (ℝ)

Distinct654
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.057484
Minimum2
Maximum999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:23.131684image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile14
Q125
median41
Q364
95-th percentile166
Maximum999
Range997
Interquartile range (IQR)39

Descriptive statistics

Standard deviation58.580993
Coefficient of variation (CV)1.0267013
Kurtosis20.173425
Mean57.057484
Median Absolute Deviation (MAD)18
Skewness3.715959
Sum13840548
Variance3431.7328
MonotonicityNot monotonic
2022-12-14T20:30:23.250058image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18 4781
 
2.0%
17 4735
 
2.0%
19 4730
 
1.9%
16 4677
 
1.9%
20 4536
 
1.9%
23 4511
 
1.9%
21 4476
 
1.8%
22 4426
 
1.8%
15 4373
 
1.8%
24 4343
 
1.8%
Other values (644) 196984
81.2%
ValueCountFrequency (%)
2 1
 
< 0.1%
3 2
 
< 0.1%
4 8
 
< 0.1%
5 14
 
< 0.1%
6 35
 
< 0.1%
7 95
 
< 0.1%
8 210
 
0.1%
9 484
 
0.2%
10 838
0.3%
11 1563
0.6%
ValueCountFrequency (%)
999 1
< 0.1%
937 1
< 0.1%
909 1
< 0.1%
889 1
< 0.1%
879 1
< 0.1%
863 1
< 0.1%
862 1
< 0.1%
836 1
< 0.1%
835 1
< 0.1%
826 1
< 0.1%

lostTopTurrets
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
145365 
1
76089 
2
21118 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 145365
59.9%
1 76089
31.4%
2 21118
 
8.7%

Length

2022-12-14T20:30:23.351786image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:23.441545image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 145365
59.9%
1 76089
31.4%
2 21118
 
8.7%

Most occurring characters

ValueCountFrequency (%)
0 145365
59.9%
1 76089
31.4%
2 21118
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 145365
59.9%
1 76089
31.4%
2 21118
 
8.7%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 145365
59.9%
1 76089
31.4%
2 21118
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 145365
59.9%
1 76089
31.4%
2 21118
 
8.7%

destroyedTopTurrets
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
144013 
1
75805 
2
22754 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 144013
59.4%
1 75805
31.3%
2 22754
 
9.4%

Length

2022-12-14T20:30:23.523326image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:23.613086image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 144013
59.4%
1 75805
31.3%
2 22754
 
9.4%

Most occurring characters

ValueCountFrequency (%)
0 144013
59.4%
1 75805
31.3%
2 22754
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144013
59.4%
1 75805
31.3%
2 22754
 
9.4%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144013
59.4%
1 75805
31.3%
2 22754
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144013
59.4%
1 75805
31.3%
2 22754
 
9.4%

lostMidTurrets
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
146058 
1
75047 
2
21467 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 146058
60.2%
1 75047
30.9%
2 21467
 
8.8%

Length

2022-12-14T20:30:23.696612image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:23.783360image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 146058
60.2%
1 75047
30.9%
2 21467
 
8.8%

Most occurring characters

ValueCountFrequency (%)
0 146058
60.2%
1 75047
30.9%
2 21467
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146058
60.2%
1 75047
30.9%
2 21467
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146058
60.2%
1 75047
30.9%
2 21467
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146058
60.2%
1 75047
30.9%
2 21467
 
8.8%

destroyedMidTurrets
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
142904 
1
78250 
2
21418 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 142904
58.9%
1 78250
32.3%
2 21418
 
8.8%

Length

2022-12-14T20:30:23.862149image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:23.948559image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 142904
58.9%
1 78250
32.3%
2 21418
 
8.8%

Most occurring characters

ValueCountFrequency (%)
0 142904
58.9%
1 78250
32.3%
2 21418
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 142904
58.9%
1 78250
32.3%
2 21418
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 142904
58.9%
1 78250
32.3%
2 21418
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 142904
58.9%
1 78250
32.3%
2 21418
 
8.8%

lostBotTurrets
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
146726 
1
58306 
2
31237 
3
 
3972
4
 
2331

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 146726
60.5%
1 58306
 
24.0%
2 31237
 
12.9%
3 3972
 
1.6%
4 2331
 
1.0%

Length

2022-12-14T20:30:24.032020image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:24.123774image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 146726
60.5%
1 58306
 
24.0%
2 31237
 
12.9%
3 3972
 
1.6%
4 2331
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 146726
60.5%
1 58306
 
24.0%
2 31237
 
12.9%
3 3972
 
1.6%
4 2331
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146726
60.5%
1 58306
 
24.0%
2 31237
 
12.9%
3 3972
 
1.6%
4 2331
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146726
60.5%
1 58306
 
24.0%
2 31237
 
12.9%
3 3972
 
1.6%
4 2331
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146726
60.5%
1 58306
 
24.0%
2 31237
 
12.9%
3 3972
 
1.6%
4 2331
 
1.0%

destroyedBotTurrets
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
0
142750 
1
59359 
2
33887 
3
 
4248
4
 
2328

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 142750
58.8%
1 59359
24.5%
2 33887
 
14.0%
3 4248
 
1.8%
4 2328
 
1.0%

Length

2022-12-14T20:30:24.208548image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:24.300302image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0 142750
58.8%
1 59359
24.5%
2 33887
 
14.0%
3 4248
 
1.8%
4 2328
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 142750
58.8%
1 59359
24.5%
2 33887
 
14.0%
3 4248
 
1.8%
4 2328
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 142750
58.8%
1 59359
24.5%
2 33887
 
14.0%
3 4248
 
1.8%
4 2328
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 142750
58.8%
1 59359
24.5%
2 33887
 
14.0%
3 4248
 
1.8%
4 2328
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 142750
58.8%
1 59359
24.5%
2 33887
 
14.0%
3 4248
 
1.8%
4 2328
 
1.0%

destroyedInhibitors
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1397111
Minimum0
Maximum8
Zeros218455
Zeros (%)90.1%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:24.379091image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.47780849
Coefficient of variation (CV)3.4199753
Kurtosis23.465575
Mean0.1397111
Median Absolute Deviation (MAD)0
Skewness4.339961
Sum33890
Variance0.22830095
MonotonicityNot monotonic
2022-12-14T20:30:24.456884image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 218455
90.1%
1 16886
 
7.0%
2 5306
 
2.2%
3 1454
 
0.6%
4 352
 
0.1%
5 98
 
< 0.1%
6 16
 
< 0.1%
7 4
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
0 218455
90.1%
1 16886
 
7.0%
2 5306
 
2.2%
3 1454
 
0.6%
4 352
 
0.1%
5 98
 
< 0.1%
6 16
 
< 0.1%
7 4
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
7 4
 
< 0.1%
6 16
 
< 0.1%
5 98
 
< 0.1%
4 352
 
0.1%
3 1454
 
0.6%
2 5306
 
2.2%
1 16886
 
7.0%
0 218455
90.1%

lostInhibitors
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.13373349
Minimum0
Maximum8
Zeros219211
Zeros (%)90.4%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:24.539382image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.46533576
Coefficient of variation (CV)3.4795754
Kurtosis25.762612
Mean0.13373349
Median Absolute Deviation (MAD)0
Skewness4.4738171
Sum32440
Variance0.21653737
MonotonicityNot monotonic
2022-12-14T20:30:24.618170image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 219211
90.4%
1 16634
 
6.9%
2 4947
 
2.0%
3 1352
 
0.6%
4 328
 
0.1%
5 71
 
< 0.1%
6 20
 
< 0.1%
8 6
 
< 0.1%
7 3
 
< 0.1%
ValueCountFrequency (%)
0 219211
90.4%
1 16634
 
6.9%
2 4947
 
2.0%
3 1352
 
0.6%
4 328
 
0.1%
5 71
 
< 0.1%
6 20
 
< 0.1%
7 3
 
< 0.1%
8 6
 
< 0.1%
ValueCountFrequency (%)
8 6
 
< 0.1%
7 3
 
< 0.1%
6 20
 
< 0.1%
5 71
 
< 0.1%
4 328
 
0.1%
3 1352
 
0.6%
2 4947
 
2.0%
1 16634
 
6.9%
0 219211
90.4%

killedElemDrakes
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
1
83090 
0
75556 
2
51656 
3
23983 
4
 
8287

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 83090
34.3%
0 75556
31.1%
2 51656
21.3%
3 23983
 
9.9%
4 8287
 
3.4%

Length

2022-12-14T20:30:24.709926image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:25.022501image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1 83090
34.3%
0 75556
31.1%
2 51656
21.3%
3 23983
 
9.9%
4 8287
 
3.4%

Most occurring characters

ValueCountFrequency (%)
1 83090
34.3%
0 75556
31.1%
2 51656
21.3%
3 23983
 
9.9%
4 8287
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 83090
34.3%
0 75556
31.1%
2 51656
21.3%
3 23983
 
9.9%
4 8287
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 83090
34.3%
0 75556
31.1%
2 51656
21.3%
3 23983
 
9.9%
4 8287
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 83090
34.3%
0 75556
31.1%
2 51656
21.3%
3 23983
 
9.9%
4 8287
 
3.4%

lostElemDrakes
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
1
82693 
0
71224 
2
53010 
3
26291 
4
9354 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters242572
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 82693
34.1%
0 71224
29.4%
2 53010
21.9%
3 26291
 
10.8%
4 9354
 
3.9%

Length

2022-12-14T20:30:25.110265image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-14T20:30:25.203017image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1 82693
34.1%
0 71224
29.4%
2 53010
21.9%
3 26291
 
10.8%
4 9354
 
3.9%

Most occurring characters

ValueCountFrequency (%)
1 82693
34.1%
0 71224
29.4%
2 53010
21.9%
3 26291
 
10.8%
4 9354
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242572
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 82693
34.1%
0 71224
29.4%
2 53010
21.9%
3 26291
 
10.8%
4 9354
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
Common 242572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 82693
34.1%
0 71224
29.4%
2 53010
21.9%
3 26291
 
10.8%
4 9354
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 82693
34.1%
0 71224
29.4%
2 53010
21.9%
3 26291
 
10.8%
4 9354
 
3.9%

obtainedDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
234285 
True
 
8287
ValueCountFrequency (%)
False 234285
96.6%
True 8287
 
3.4%
2022-12-14T20:30:25.293774image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

lostDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
233218 
True
 
9354
ValueCountFrequency (%)
False 233218
96.1%
True 9354
 
3.9%
2022-12-14T20:30:25.367577image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

obtainedFireDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
238410 
True
 
4162
ValueCountFrequency (%)
False 238410
98.3%
True 4162
 
1.7%
2022-12-14T20:30:25.442376image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

obtainedWaterDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
238134 
True
 
4438
ValueCountFrequency (%)
False 238134
98.2%
True 4438
 
1.8%
2022-12-14T20:30:25.516181image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

obtainedAirDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
238092 
True
 
4480
ValueCountFrequency (%)
False 238092
98.2%
True 4480
 
1.8%
2022-12-14T20:30:25.597961image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

obtainedEarthDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
237907 
True
 
4665
ValueCountFrequency (%)
False 237907
98.1%
True 4665
 
1.9%
2022-12-14T20:30:25.679741image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

lostFireDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
238291 
True
 
4281
ValueCountFrequency (%)
False 238291
98.2%
True 4281
 
1.8%
2022-12-14T20:30:25.754547image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

lostWaterDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
237939 
True
 
4633
ValueCountFrequency (%)
False 237939
98.1%
True 4633
 
1.9%
2022-12-14T20:30:25.826350image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

lostAirDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
237943 
True
 
4629
ValueCountFrequency (%)
False 237943
98.1%
True 4629
 
1.9%
2022-12-14T20:30:25.895166image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

lostEarthDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
237657 
True
 
4915
ValueCountFrequency (%)
False 237657
98.0%
True 4915
 
2.0%
2022-12-14T20:30:25.965007image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

GameFireDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
234411 
True
 
8161
ValueCountFrequency (%)
False 234411
96.6%
True 8161
 
3.4%
2022-12-14T20:30:26.035428image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

GameWaterDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
233796 
True
 
8776
ValueCountFrequency (%)
False 233796
96.4%
True 8776
 
3.6%
2022-12-14T20:30:26.106238image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

GameAirDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
233786 
True
 
8786
ValueCountFrequency (%)
False 233786
96.4%
True 8786
 
3.6%
2022-12-14T20:30:26.180042image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

GameEarthDrakeSoul
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.0 KiB
False
233300 
True
 
9272
ValueCountFrequency (%)
False 233300
96.2%
True 9272
 
3.8%
2022-12-14T20:30:26.251849image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

totalKilledObjectives
Real number (ℝ)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9128383
Minimum0
Maximum11
Zeros51268
Zeros (%)21.1%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:26.322660image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6359771
Coefficient of variation (CV)0.8552616
Kurtosis0.34263965
Mean1.9128383
Median Absolute Deviation (MAD)1
Skewness0.86625774
Sum464001
Variance2.6764211
MonotonicityNot monotonic
2022-12-14T20:30:26.408323image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 65911
27.2%
0 51268
21.1%
2 49607
20.5%
3 34913
14.4%
4 20887
 
8.6%
5 12252
 
5.1%
6 5346
 
2.2%
7 1943
 
0.8%
8 365
 
0.2%
9 69
 
< 0.1%
Other values (2) 11
 
< 0.1%
ValueCountFrequency (%)
0 51268
21.1%
1 65911
27.2%
2 49607
20.5%
3 34913
14.4%
4 20887
 
8.6%
5 12252
 
5.1%
6 5346
 
2.2%
7 1943
 
0.8%
8 365
 
0.2%
9 69
 
< 0.1%
ValueCountFrequency (%)
11 1
 
< 0.1%
10 10
 
< 0.1%
9 69
 
< 0.1%
8 365
 
0.2%
7 1943
 
0.8%
6 5346
 
2.2%
5 12252
 
5.1%
4 20887
8.6%
3 34913
14.4%
2 49607
20.5%

totalLostObjectives
Real number (ℝ)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0387761
Minimum0
Maximum11
Zeros49181
Zeros (%)20.3%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:26.496088image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7236575
Coefficient of variation (CV)0.84543736
Kurtosis0.12470898
Mean2.0387761
Median Absolute Deviation (MAD)1
Skewness0.81114018
Sum494550
Variance2.9709952
MonotonicityNot monotonic
2022-12-14T20:30:26.577872image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 62501
25.8%
0 49181
20.3%
2 47918
19.8%
3 34858
14.4%
4 23266
 
9.6%
5 14588
 
6.0%
6 6950
 
2.9%
7 2652
 
1.1%
8 562
 
0.2%
9 86
 
< 0.1%
Other values (2) 10
 
< 0.1%
ValueCountFrequency (%)
0 49181
20.3%
1 62501
25.8%
2 47918
19.8%
3 34858
14.4%
4 23266
 
9.6%
5 14588
 
6.0%
6 6950
 
2.9%
7 2652
 
1.1%
8 562
 
0.2%
9 86
 
< 0.1%
ValueCountFrequency (%)
11 1
 
< 0.1%
10 9
 
< 0.1%
9 86
 
< 0.1%
8 562
 
0.2%
7 2652
 
1.1%
6 6950
 
2.9%
5 14588
 
6.0%
4 23266
9.6%
3 34858
14.4%
2 47918
19.8%

totalGameKilledObjectives
Real number (ℝ)

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9516144
Minimum0
Maximum14
Zeros5812
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:26.664332image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q36
95-th percentile8
Maximum14
Range14
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.2916291
Coefficient of variation (CV)0.57992225
Kurtosis-0.32063015
Mean3.9516144
Median Absolute Deviation (MAD)2
Skewness0.49036447
Sum958551
Variance5.2515639
MonotonicityNot monotonic
2022-12-14T20:30:26.747929image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3 43187
17.8%
2 38074
15.7%
5 34723
14.3%
1 30940
12.8%
4 28692
11.8%
6 23792
9.8%
7 20331
8.4%
8 8963
 
3.7%
0 5812
 
2.4%
9 5109
 
2.1%
Other values (5) 2949
 
1.2%
ValueCountFrequency (%)
0 5812
 
2.4%
1 30940
12.8%
2 38074
15.7%
3 43187
17.8%
4 28692
11.8%
5 34723
14.3%
6 23792
9.8%
7 20331
8.4%
8 8963
 
3.7%
9 5109
 
2.1%
ValueCountFrequency (%)
14 5
 
< 0.1%
13 44
 
< 0.1%
12 222
 
0.1%
11 679
 
0.3%
10 1999
 
0.8%
9 5109
 
2.1%
8 8963
 
3.7%
7 20331
8.4%
6 23792
9.8%
5 34723
14.3%

totalLostTurrets
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5596441
Minimum0
Maximum8
Zeros95544
Zeros (%)39.4%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:26.835696image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum8
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7167541
Coefficient of variation (CV)1.1007345
Kurtosis0.18230339
Mean1.5596441
Median Absolute Deviation (MAD)1
Skewness0.98510329
Sum378326
Variance2.9472446
MonotonicityNot monotonic
2022-12-14T20:30:26.920467image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 95544
39.4%
1 45703
18.8%
2 35527
 
14.6%
3 28248
 
11.6%
4 19705
 
8.1%
5 11192
 
4.6%
6 4870
 
2.0%
7 1439
 
0.6%
8 344
 
0.1%
ValueCountFrequency (%)
0 95544
39.4%
1 45703
18.8%
2 35527
 
14.6%
3 28248
 
11.6%
4 19705
 
8.1%
5 11192
 
4.6%
6 4870
 
2.0%
7 1439
 
0.6%
8 344
 
0.1%
ValueCountFrequency (%)
8 344
 
0.1%
7 1439
 
0.6%
6 4870
 
2.0%
5 11192
 
4.6%
4 19705
 
8.1%
3 28248
 
11.6%
2 35527
 
14.6%
1 45703
18.8%
0 95544
39.4%

totalDestroyedTurrets
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6143166
Minimum0
Maximum8
Zeros92814
Zeros (%)38.3%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:27.012221image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum8
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7377158
Coefficient of variation (CV)1.0764405
Kurtosis0.029514532
Mean1.6143166
Median Absolute Deviation (MAD)1
Skewness0.9272023
Sum391588
Variance3.0196561
MonotonicityNot monotonic
2022-12-14T20:30:27.093007image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 92814
38.3%
1 45036
18.6%
2 35645
 
14.7%
3 29087
 
12.0%
4 20942
 
8.6%
5 12202
 
5.0%
6 5069
 
2.1%
7 1407
 
0.6%
8 370
 
0.2%
ValueCountFrequency (%)
0 92814
38.3%
1 45036
18.6%
2 35645
 
14.7%
3 29087
 
12.0%
4 20942
 
8.6%
5 12202
 
5.0%
6 5069
 
2.1%
7 1407
 
0.6%
8 370
 
0.2%
ValueCountFrequency (%)
8 370
 
0.2%
7 1407
 
0.6%
6 5069
 
2.1%
5 12202
 
5.0%
4 20942
 
8.6%
3 29087
 
12.0%
2 35645
 
14.7%
1 45036
18.6%
0 92814
38.3%

totalLostStructures
Real number (ℝ)

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6933776
Minimum0
Maximum14
Zeros95505
Zeros (%)39.4%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:27.180771image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6
Maximum14
Range14
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9920795
Coefficient of variation (CV)1.1763941
Kurtosis1.6320877
Mean1.6933776
Median Absolute Deviation (MAD)1
Skewness1.3516845
Sum410766
Variance3.9683806
MonotonicityNot monotonic
2022-12-14T20:30:27.263555image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 95505
39.4%
1 45319
18.7%
2 34231
 
14.1%
3 25548
 
10.5%
4 17254
 
7.1%
5 10673
 
4.4%
6 6481
 
2.7%
7 3847
 
1.6%
8 2067
 
0.9%
9 1104
 
0.5%
Other values (5) 543
 
0.2%
ValueCountFrequency (%)
0 95505
39.4%
1 45319
18.7%
2 34231
 
14.1%
3 25548
 
10.5%
4 17254
 
7.1%
5 10673
 
4.4%
6 6481
 
2.7%
7 3847
 
1.6%
8 2067
 
0.9%
9 1104
 
0.5%
ValueCountFrequency (%)
14 7
 
< 0.1%
13 8
 
< 0.1%
12 33
 
< 0.1%
11 125
 
0.1%
10 370
 
0.2%
9 1104
 
0.5%
8 2067
 
0.9%
7 3847
 
1.6%
6 6481
2.7%
5 10673
4.4%

totalDestroyedStructures
Real number (ℝ)

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7540277
Minimum0
Maximum14
Zeros92761
Zeros (%)38.2%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:27.349319image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6
Maximum14
Range14
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0193806
Coefficient of variation (CV)1.1512821
Kurtosis1.4028234
Mean1.7540277
Median Absolute Deviation (MAD)1
Skewness1.291902
Sum425478
Variance4.0778981
MonotonicityNot monotonic
2022-12-14T20:30:27.432518image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 92761
38.2%
1 44697
18.4%
2 34402
 
14.2%
3 26284
 
10.8%
4 18189
 
7.5%
5 11470
 
4.7%
6 6757
 
2.8%
7 4075
 
1.7%
8 2310
 
1.0%
9 1009
 
0.4%
Other values (5) 618
 
0.3%
ValueCountFrequency (%)
0 92761
38.2%
1 44697
18.4%
2 34402
 
14.2%
3 26284
 
10.8%
4 18189
 
7.5%
5 11470
 
4.7%
6 6757
 
2.8%
7 4075
 
1.7%
8 2310
 
1.0%
9 1009
 
0.4%
ValueCountFrequency (%)
14 2
 
< 0.1%
13 7
 
< 0.1%
12 26
 
< 0.1%
11 130
 
0.1%
10 453
 
0.2%
9 1009
 
0.4%
8 2310
 
1.0%
7 4075
 
1.7%
6 6757
2.8%
5 11470
4.7%

totalGameDestroyedStructures
Real number (ℝ)

Distinct22
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4474053
Minimum0
Maximum21
Zeros56534
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2022-12-14T20:30:27.528263image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q35
95-th percentile9
Maximum21
Range21
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.0455047
Coefficient of variation (CV)0.88341939
Kurtosis0.029148713
Mean3.4474053
Median Absolute Deviation (MAD)2
Skewness0.73918533
Sum836244
Variance9.2750988
MonotonicityNot monotonic
2022-12-14T20:30:27.615031image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 56534
23.3%
1 26925
11.1%
4 25984
10.7%
3 25765
10.6%
2 23994
9.9%
5 23488
9.7%
6 19000
 
7.8%
7 14272
 
5.9%
8 10359
 
4.3%
9 6892
 
2.8%
Other values (12) 9359
 
3.9%
ValueCountFrequency (%)
0 56534
23.3%
1 26925
11.1%
2 23994
9.9%
3 25765
10.6%
4 25984
10.7%
5 23488
9.7%
6 19000
 
7.8%
7 14272
 
5.9%
8 10359
 
4.3%
9 6892
 
2.8%
ValueCountFrequency (%)
21 1
 
< 0.1%
20 2
 
< 0.1%
19 12
 
< 0.1%
18 7
 
< 0.1%
17 26
 
< 0.1%
16 83
 
< 0.1%
15 162
 
0.1%
14 336
 
0.1%
13 658
0.3%
12 1311
0.5%

Missing values

2022-12-14T20:30:08.697455image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

gameIdgameDurationhasWonframegoldDiffexpDiffchampLevelDiffisFirstTowerisFirstBloodkilledFireDrakekilledWaterDrakekilledAirDrakekilledEarthDrakekilledElderDrakelostFireDrakelostWaterDrakelostAirDrakelostEarthDrakelostElderDrakekilledBaronNashorlostBaronNashorkilledRiftHeraldlostRiftHeralddestroyedTopInhibitordestroyedMidInhibitordestroyedBotInhibitorlostTopInhibitorlostMidInhibitorlostBotInhibitordestroyedTopNexusTurretdestroyedMidNexusTurretdestroyedBotNexusTurretlostTopNexusTurretlostMidNexusTurretlostBotNexusTurretdestroyedTopBaseTurretdestroyedMidBaseTurretdestroyedBotBaseTurretlostTopBaseTurretlostMidBaseTurretlostBotBaseTurretdestroyedTopInnerTurretdestroyedMidInnerTurretdestroyedBotInnerTurretlostTopInnerTurretlostMidInnerTurretlostBotInnerTurretdestroyedTopOuterTurretdestroyedMidOuterTurretdestroyedBotOuterTurretlostTopOuterTurretlostMidOuterTurretlostBotOuterTurretkillsdeathsassistswardsPlacedwardsDestroyedwardsLostKDAvisionScoreimprovedVisionScorelostTopTurretsdestroyedTopTurretslostMidTurretsdestroyedMidTurretslostBotTurretsdestroyedBotTurretsdestroyedInhibitorslostInhibitorskilledElemDrakeslostElemDrakesobtainedDrakeSoullostDrakeSoulobtainedFireDrakeSoulobtainedWaterDrakeSoulobtainedAirDrakeSoulobtainedEarthDrakeSoullostFireDrakeSoullostWaterDrakeSoullostAirDrakeSoullostEarthDrakeSoulGameFireDrakeSoulGameWaterDrakeSoulGameAirDrakeSoulGameEarthDrakeSoultotalKilledObjectivestotalLostObjectivestotalGameKilledObjectivestotalLostTurretstotalDestroyedTurretstotalLostStructurestotalDestroyedStructurestotalGameDestroyedStructures
045462331261443000110-448-147-0.2010001000000000000000000000000000000000000000047521351.28571424190000000010FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse10100000
145462331261443000112-1306-925-0.60100010010000001000000000000000000000000000000611628461.09090932260000000011FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse12300000
245462331261443000114211525780.4110001001000000100000000000000000000000010000010111235462.00000039330100000011FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse12301011
345462331261443000116119521340.41100010010000001000000000000000000000000100010101212456101.83333351410110000011FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse12311112
445462331261443000118293143820.61110010010000001000000000000000000000000100010131316497122.23076956440110000021FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse22411112
545462331261443000120612776060.81110010010000011000000000000000000000000101010201428639133.42857172590110010021FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse32512123
645462331261443000122742878421.411100100100000110010000010000000000010001010102315337510133.73333385720110021021FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse32513145
7454623312614430001249426119801.811200100100010110010000010000000000010001010102615368511144.13333396820110021031FalseFalseTrueFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalse52713145
8443821266312410001108989340.0010000000000000000000000000000000000000000000066715412.16666719180000000000FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse00000000
944382126631241000112126315660.4010000001000000000000000000000000000000000000077720542.00000025210000000001FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse01100000
gameIdgameDurationhasWonframegoldDiffexpDiffchampLevelDiffisFirstTowerisFirstBloodkilledFireDrakekilledWaterDrakekilledAirDrakekilledEarthDrakekilledElderDrakelostFireDrakelostWaterDrakelostAirDrakelostEarthDrakelostElderDrakekilledBaronNashorlostBaronNashorkilledRiftHeraldlostRiftHeralddestroyedTopInhibitordestroyedMidInhibitordestroyedBotInhibitorlostTopInhibitorlostMidInhibitorlostBotInhibitordestroyedTopNexusTurretdestroyedMidNexusTurretdestroyedBotNexusTurretlostTopNexusTurretlostMidNexusTurretlostBotNexusTurretdestroyedTopBaseTurretdestroyedMidBaseTurretdestroyedBotBaseTurretlostTopBaseTurretlostMidBaseTurretlostBotBaseTurretdestroyedTopInnerTurretdestroyedMidInnerTurretdestroyedBotInnerTurretlostTopInnerTurretlostMidInnerTurretlostBotInnerTurretdestroyedTopOuterTurretdestroyedMidOuterTurretdestroyedBotOuterTurretlostTopOuterTurretlostMidOuterTurretlostBotOuterTurretkillsdeathsassistswardsPlacedwardsDestroyedwardsLostKDAvisionScoreimprovedVisionScorelostTopTurretsdestroyedTopTurretslostMidTurretsdestroyedMidTurretslostBotTurretsdestroyedBotTurretsdestroyedInhibitorslostInhibitorskilledElemDrakeslostElemDrakesobtainedDrakeSoullostDrakeSoulobtainedFireDrakeSoulobtainedWaterDrakeSoulobtainedAirDrakeSoulobtainedEarthDrakeSoullostFireDrakeSoullostWaterDrakeSoullostAirDrakeSoullostEarthDrakeSoulGameFireDrakeSoulGameWaterDrakeSoulGameAirDrakeSoulGameEarthDrakeSoultotalKilledObjectivestotalLostObjectivestotalGameKilledObjectivestotalLostTurretstotalDestroyedTurretstotalLostStructurestotalDestroyedStructurestotalGameDestroyedStructures
24256244021564831774000020144014640.411000001011000020000000000000000000001000100102317374811113.52941259481011000003FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse05521213
2425634402156483177400002212916340.211000001011000020000000000000000000001000100102520415411123.30000065531011000003FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse05521213
24256444021564831774000024-1321-2549-0.411000001011000020000000000000000000001000100112928455712122.64285769571011100003FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse05531314
24256544021564831774000026-4062-5239-0.811100001011000020000000000000000000001000100113032476714152.40625081661011100013FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse15631314
24256644021564831774000028-5640-9016-1.011100001011001020000000000000000000001000100113336507415162.30555689731011100013FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse16731314
24256744021564831774000030-8523-13498-1.611100001011001020000010000000000020001000100113341508018172.02439098811011300113FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse16751617
24256843798267391013000010-271-1243-0.2010100000000000000000000000000000000000000000065618122.40000019170000000010FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse10100000
24256943798267391013000012-2013-3493-0.8010100000000000000000000000000000000000000000078623151.62500024190000000010FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse10100000
24257043798267391013000014-2388-4543-0.801010000000000000000000000000000000000000000001013927561.46153832260000000010FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse10100000
24257143798267391013000016-5601-7595-1.20101000000100000000000000000000000000000000000111710316101.23529437270000000011FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse11200000